Designing A Cement Slurry With A Young&#39;s Modulus Requirement

ABSTRACT

A method of generating a wellbore treatment fluid comprising: obtaining a target Young&#39;s modulus; calculating a compressive strength requirement from a correlation comprising compressive strength and Young&#39;s modulus using the target Young&#39;s modulus as an input; classifying a plurality of solid particulates using correlations; calculating a reactive index and/or a water requirement for at least one of the solid particulates; and selecting two or more solid particulates from the plurality of solid particulates to create a wellbore treatment fluid, wherein two or more solid particulates are selected such that when the wellbore treatment fluid is prepared and set, the set wellbore treatment fluid has a 24 hour compressive strength greater than or equal to the compressive strength requirement.

BACKGROUND

In well cementing, such as well construction and remedial cementing, cement compositions are commonly utilized. Cement compositions may be used in a variety of subterranean applications. For example, in subterranean well construction, a pipe string (e.g., casing, liners, expandable tubulars, etc.) may be run into a well bore and cemented in place. The process of cementing the pipe string in place is commonly referred to as “primary cementing.” In a typical primary cementing method, a cement composition may be pumped into an annulus between the walls of the well bore and the exterior surface of the pipe string disposed therein. The cement composition may set in the annular space, thereby forming an annular sheath of hardened, substantially impermeable cement (i.e., a cement sheath) that may support and position the pipe string in the well bore and may bond the exterior surface of the pipe string to the subterranean formation. Among other things, the cement sheath surrounding the pipe string functions to prevent the migration of fluids in the annulus, as well as protecting the pipe string from corrosion. Cement compositions also may be used in remedial cementing methods, for example, to seal cracks or holes in pipe strings or cement sheaths, to seal highly permeable formation zones or fractures, to place a cement plug, and the like.

A particular challenge in well cementing is the development of satisfactory mechanical properties in a cement composition within a reasonable time period after placement in the subterranean formation. Oftentimes several cement compositions with varying additives are tested to see if they meet the material engineering requirements for a particular well. The process of selecting the components of the cement composition are usually done by a best guess approach by utilizing previous slurries and modifying them until a satisfactory solution is reached. The process may be time consuming and the resulting slurry may be expensive. Furthermore, the cement components available in any one particular region may vary in composition from those of another region thereby further complicating the process of selecting a correct slurry.

BRIEF DESCRIPTION OF THE DRAWINGS

These drawings illustrate certain aspects of some of the embodiments of the present invention, and should not be used to limit or define the invention.

FIG. 1 is a chart showing simulated results for compressive strength index calculations.

FIG. 2 is a chart showing simulated results for compressive strength index calculations.

FIG. 3 is a schematic illustration of an example system for analyzing cement components.

FIG. 4 is a schematic illustration of an example system for generating cement compositions.

FIG. 5 is a schematic illustration of showing introduction of a cement composition into a wellbore.

FIG. 6 is a graph of predicted Young's modulus versus observed Young's modulus for a cement composition.

FIG. 7 is a graph of predicted Young's modulus versus observed Young's modulus for a cement composition.

DETAILED DESCRIPTION

The present disclosure may generally relate to cementing methods and systems. Provided herein are methods that may include identifying and categorizing silica sources, cements, and other materials based on physiochemical properties. In some examples, the silica sources may be considered inorganic particles. The inorganic particles may or may not comprise silica and may comprise other minerals such as alumina and other oxides. The physiochemical properties of each cement component of a cement composition may affect the final set mechanical properties of the slurry such as Young's modulus as well as the dynamic or time based properties such as mixability, rheology, viscosity, and others. Every cement component may affect one or more of the properties mentioned, sometimes unpredictably. For example, a locally sourced fly ash may be added to a cement composition. The added fly ash may increase the compressive strength of the cement composition and may have no effect on for example, the thickening time of the cement composition. In another region, a locally sourced fly ash may also increase the compressive strength of the cement composition but may also increase the thickening time. The unpredictable behavior of a cement composition may not be realized until multiple lab tests have been performed.

Furthermore, designing a cement composition generally requires certain target parameters to be achieved, such as compressive strength in the final set cement. Whether by regulatory requirements or customer requirements compressive strength may be a strong determining factor of whether a certain cement composition performs are required and will be selected to be pumped into a wellbore. A cement composition which is designed with compressive strength as a main design requirement may result in a cement composition that is overdesigned with respect to compressive strength which may result in higher cost of goods sold (“COGS”) than may be necessary. Additionally, a cement with a relatively high compressive strength may result in relatively less ductility in the final cement sheath. Generally speaking, ductility increases as Young's Modulus decreases. Thus, exceeding the necessary compressive strength requirement of a cement sheath, may result in premature failure of the cement sheath due to lower ductility, potentially requiring additional remedial cement work to repair. Cement compositions designed primarily with compressive strength may result in additional additives being used which in turn may result in a higher cost of the cement composition.

A method presented herein may comprise designing a cement composition with Young's modulus as a design requirement. Various chemical additives may be used to modulate the Young's modulus of a particular cement composition. These chemical additives may be costly, may not be compatible with all wellbores, and may result in additional equipment cost associated with transportation and storage among other potentially negatives. Young's Modulus may also be modulated by changing the composition of the cement such as by increasing or reducing a particular cementitious component. Generally, designing a well bore cement slurry for Young's modulus can increase cost and time required to design and test. However, following techniques disclosed herein can minimize the COGS and also minimize the time required to develop appropriate cement slurry formulations.

The method may be combined with other slurry design processes to select the cementitious components that produce the required Young's modulus and by extension, design a cement composition with a selected compressive strength. The method may correlate a Young's modulus of a set cement from compressive strength and density of the cement composition for a wide range of temperatures, densities, and composition portfolios of bulk blends of cements.

The cement compositions generally may comprise water and a cement additive. The cement additive may comprise two or more cement components, which may be dry blended to form the cement additive prior to combination with the water. Alternatively, the cement components may not be combined until the mixture is combined with the water. The cement components may generally be described as alkali soluble. A cement composition may comprise water and a cement additive, wherein the cement additive may comprise one or more of hydraulic cement, cement kiln dust, and a natural pozzolan. As described in more detail herein, the cement compositions may be foamed and/or extended as desired by those of ordinary skill in the art.

The cement compositions may have a density suitable for a particular application. The cement compositions may have any suitable density, including, but not limited to, in the range of about 8 pounds per gallon (“ppg”) to about 16 ppg (1 g/cm³ to 1.9 g/cm³). In the foamed examples, the cement compositions may have a density in the range of about 8 ppg to about 13 ppg (1 g/cm³ to 1.6 g/cm³) (or even lower). It should be understood that the present techniques should also encompass the use of cement compositions with densities outside the specific ranges disclosed herein.

The water used in the cement compositions may include, for example, freshwater, saltwater (e.g., water containing one or more salts dissolved therein), brine (e.g., saturated saltwater produced from subterranean formations), seawater, or combinations thereof. Generally, the water may be from any source, provided that it does not contain an excess of compounds that may undesirably affect other components in the cement composition. The water may be included in an amount sufficient to form a pumpable slurry. The water may be included in the cement compositions in any suitable range, including, but not limited to, in the range of about 40% to about 200% by weight of the cement additive (“bwoc”). In some examples, the water may be included in an amount in the range of about 40% to about 150% bwoc.

The cement additive may comprise two or more cement components. One of the cement components may comprise a hydraulic cement. A variety of hydraulic cements may be utilized in accordance with the present disclosure, including, but not limited to, those comprising calcium, aluminum, silicon, oxygen, iron, and/or sulfur, which set and harden by reaction with water. Suitable hydraulic cements may include Portland cements, gypsum, and high alumina content cements, among others. Portland cements that are suited for use in the present disclosure may be classified as Classes A, C, G, and H cements according to American Petroleum Institute, API Specification for Materials and Testing for Well Cements, API Specification 10, Fifth Ed., Jul. 1, 1990. In addition, in some examples, cements suitable for use in the present invention may be classified as ASTM Type I, II, or III. Cement compositions that may be considered “low Portland” may be designed by use of the techniques disclosed herein.

Where present, the hydraulic cement generally may be included in the cement compositions in an amount sufficient to provide the desired compressive strength, density, and/or cost. The hydraulic cement may be present in the cement compositions in any suitable amount, including, but not limited to, in the range of about 0% to about 99% bwoc. In some examples the hydraulic cement may be present in an amount ranging between any of and/or including any of about 1%, about 5%, about 10%, about 20%, about 40%, about 60%, about 80%, or about 90% bwoc. Cement composition that are considered “low Portland” may be used, in that the Portland cement (where used) may be present in the cement composition in an amount of about 40% or less bwoc and, alternatively, about 10% or less. In addition, the cement compositions may also be designed that are free (or essentially free) of Portland cement. Those of ordinary skill in the art, with the benefit of this disclosure, should be able to select an appropriate amount of hydraulic cement for a particular application.

In addition to hydraulic cement, additional cement components may be used that can be considered alkali soluble. A cement component is considered alkali soluble where it is at least partially soluble in an aqueous solution of pH 7.0 or greater. Certain of the alkali soluble cement components may comprise a geopolymer cement, which may comprise an aluminosilicate source, a metal silicate source, and an activator. The geopolymer cement may react to form a geopolymer. A geopolymer is an inorganic polymer that forms long-range, covalently bonded, non-crystalline networks. Geopolymers may be formed by chemical dissolution and subsequent re-condensation of various aluminosilicates and silicates to form a 3D-network or three-dimensional mineral polymer.

The activator for the geopolymer cement may include, but is not limited to, metal hydroxides chloride salts such as KCl, CaCl₂, NaCl, carbonates such as Na₂CO₃, silicates such as sodium silicate, aluminates such as sodium aluminate, and ammonium hydroxide.

The aluminosilicate source for the geopolymer cement may comprise any suitable aluminosilicate. Aluminosilicate is a mineral comprising aluminum, silicon, and oxygen, plus counter-cations. There are potentially hundreds of suitable minerals that may be an aluminosilicate source in that they may comprise aluminosilicate minerals. Each aluminosilicate source may potentially be used in a particular case if the specific properties, such as composition, may be known. Some minerals such as andalusite, kyanite, and sillimanite are naturally occurring aluminosilicate sources that have the same composition, Al₂SiO₅, but differ in crystal structure. Each mineral andalusite, kyanite, or sillimanite may react more or less quickly and to different extents at the same temperature and pressure due to the differing crystal structures. Other suitable aluminosilicate sources may include, but are not limited to, calcined clays, partially calcined clays, kaolinite clays, lateritic clays, illite clays, volcanic rocks, mine tailings, blast furnace slag, and coal fly ash.

The metal silicate source for the geopolymer cement may comprise any suitable metal silicate. A silicate is a compound containing an anionic silicon compound. Some examples of a silicate include the orthosilicate anion also known as silicon tetroxide anion, SiO₄ ⁴⁻ as well as hexafluorosilicate [SiF₆]²⁻. Other common silicates include cyclic and single chain silicates which may have the general formula [SiO_(2+n)]^(2n−) and sheet-forming silicates ([SiO_(2.5)]⁻)_(n). Each silicate example may have one or more metal cations associated with each silicate molecule. Some suitable metal silicate sources and may include, without limitation, sodium silicate, magnesium silicate, and potassium silicate.

Where present, the geopolymer cement generally may be included in the cement compositions in an amount sufficient to provide the desired compressive strength, density, young's modulus, and/or cost. The geopolymer cement may be present in the cement compositions any suitable amount, including, but not limited to, in an amount in the range of about 0% to about 99% bwoc. In some examples the geopolymer cement may be present in an amount ranging between any of and/or including any of about 1%, about 5%, about 10%, about 20%, about 40%, about 60%, about 80%, or about 90% bwoc. Those of ordinary skill in the art, with the benefit of this disclosure, should be able to select an appropriate amount of geopolymer cement for a particular application.

Additional cement components that are alkali soluble may be considered a silica source. As used herein, silica has the plain and ordinary meaning of silicon dioxide (SiO₂). By inclusion of the silica source, a different path may be used to arrive at a similar product as from Portland cement. For example, a pozzolanic reaction may be induced wherein silicic acid (H₄SiO₄) and portlandite (Ca(OH)₂ react to form a cement product (calcium silicate hydrate). If other compounds, such as, aluminate, are present in the silica source, additional reactions may occur to form additional cement products, such as calcium aluminate hydrates. Additionally, alumina may be present in the silica source. As used herein, alumina is understood to have the plain and ordinary meaning of aluminum oxide (Al₂O₃). Calcium hydroxide necessary for the reaction may be provide from other cement components, such as Portland cement, or may be separately added to the cement composition. Examples of suitable silica sources may include fly ash, slag, silica fume, crystalline silica, silica flour, cement kiln dust (“CKD”), volcanic rock, perlite, metakaolin, diatomaceous earth, zeolite, shale, and agricultural waste ash (e.g., rice husk ash, sugar cane ash, and bagasse ash), among other. Some specific examples of the silica source will be discussed in more detail below. Where present, the silica source generally may be included in the cement compositions in an amount sufficient to provide the desired compressive strength, density, and/or cost. The silica source may be present in the cement compositions in any suitable amount, including, but not limited to an amount in the range of about 0% to about 99% bwoc. In some examples the silica source may be present in an amount ranging between any of and/or including any of about 1%, about 5%, about 10%, about 20%, about 40%, about 60%, about 80%, or about 90% bwoc. Those of ordinary skill in the art, with the benefit of this disclosure, should be able to select an appropriate amount of silica source for a particular application.

An example of a suitable silica source may comprise fly ash. A variety of fly ash may be suitable, including fly ash classified as Class C and Class F fly ash according to American Petroleum Institute, API Specification for Materials and Testing for Well Cements, API Specification 10, Fifth Ed., Jul. 1, 1990. Class C fly ash comprises both silica and lime, so it may set to form a hardened mass upon mixing with water. Class F fly ash generally does not contain a sufficient amount of lime to induce a cementitious reaction, therefore, an additional source of calcium ions is necessary for a set-delayed cement composition comprising Class F fly ash. In some embodiments, lime may be mixed with Class F fly ash in an amount in the range of about 0.1% to about 100% by weight of the fly ash. In some instances, the lime may be hydrated lime. Suitable examples of fly ash include, but are not limited to, POZMIX® A cement additive, commercially available from Halliburton Energy Services, Inc., Houston, Tex.

Amorphous silica may also be present. Amorphous silica may prevent strength retrogression. In general, amorphous silica may not require temperatures above 235° F. (112.77° C.) to participate in cement hydrations. Amorphous silica may protect against strength retrogression and maximize design efficiency by eliminating the need for multiple designs at different temperatures. Amorphous silica may also replace crystalline silica in some applications.

Another example of a suitable silica source may comprise slag. Slag is generally a by-product in the production of various metals from their corresponding ores. By way of example, the production of cast iron can produce slag as a granulated, blast furnace by-product with the slag generally comprising the oxidized impurities found in iron ore. Slag generally does not contain sufficient basic material, so slag cement may be used that further may comprise a base to produce a settable composition that may react with water to set to form a hardened mass. Examples of suitable sources of bases include, but are not limited to, sodium hydroxide, sodium bicarbonate, sodium carbonate, lime, and combinations thereof.

Another example of a suitable silica source may comprise CKD. Cement kiln dust or “CKD”, as that term is used herein, refers to a partially calcined kiln feed which is removed from the gas stream and collected, for example, in a dust collector during the manufacture of cement. Usually, large quantities of CKD are collected in the production of cement that are commonly disposed of as waste. Disposal of the CKD as waste can add undesirable costs to the manufacture of the cement, as well as the environmental concerns associated with its disposal. CKD is another component that may be included in examples of the cement compositions.

Another example of a suitable silica source may comprise volcanic rock. Certain volcanic rocks may exhibit cementitious properties, in that it may set and harden in the presence of hydrated lime and water. The volcanic rock may also be ground, for example. Generally, the volcanic rock may have any particle size distribution as desired for a particular application. In certain embodiments, the volcanic rock may have a mean particle size in a range of from about 1 micron to about 200 microns. The mean particle size corresponds to d50 values as measured by particle size analyzers such as those manufactured by Malvern Instruments, Worcestershire, United Kingdom. One of ordinary skill in the art, with the benefit of this disclosure, should be able to select a particle size for the volcanic rock suitable for a chosen application.

Another example of a suitable silica source may comprise metakaolin. Generally, metakaolin is a white pozzolan that may be prepared by heating kaolin clay, for example, to temperatures in the range of about 1112° F. (600° C.) to about 1472° F. (800° C.).

Another example of a suitable silica source may comprise shale. Among other things, shale included in the cement compositions may react with excess lime to form a suitable cementing material, for example, calcium silicate hydrate. A variety of shales are suitable, including those comprising silicon, aluminum, calcium, and/or magnesium. An example of a suitable shale comprises vitrified shale. Generally, the shale may have any particle size distribution as desired for a particular application. In certain embodiments, the shale may have a particle size distribution in the range of about 37 micrometers to about 4,750 micrometers.

Another example of a suitable silica source may comprise zeolite. Zeolites generally are porous alumino-silicate minerals that may be either a natural or synthetic material. Synthetic zeolites are based on the same type of structural cell as natural zeolites, and may comprise aluminosilicate hydrates. As used herein, the term “zeolite” refers to all natural and synthetic forms of zeolite. Examples of zeolites may include, without limitation, mordenite, zsm-5, zeolite x, zeolite y, zeolite a, etc. Furthermore, examples comprising zeolite may comprise zeolite in combination with a cation such as Na⁺, K⁺, Ca²⁺, Mg²⁺, etc. Zeolites comprising cations such as sodium may also provide additional cation sources to the cement composition as the zeolites dissolve.

The cement compositions may further comprise hydrated lime. As used herein, the term “hydrated lime” will be understood to mean calcium hydroxide. In some examples, the hydrated lime may be provided as quicklime (calcium oxide) which hydrates when mixed with water to form the hydrated lime. The hydrated lime may be included in examples of the cement compositions, for example, to form a hydraulic composition with the silica source. For example, the hydrated lime may be included in a silica source-to-hydrated-lime weight ratio of about 10:1 to about 1:1 or a ratio of about 3:1 to about 5:1. Where present, the hydrated lime may be included in the cement compositions in an amount in the range of from about 10% to about 100% by weight of the silica source, for example. In some examples, the hydrated lime may be present in an amount ranging between any of and/or including any of about 10%, about 20%, about 40%, about 60%, about 80%, or about 100% by weight of the silica source. One of ordinary skill in the art, with the benefit of this disclosure, should recognize the appropriate amount of hydrated lime to include for a chosen application.

In some examples, the cement compositions may comprise a calcium source other than hydrated lime. In general, calcium and a high pH, for example a pH of 7.0 or greater, may be needed for certain cementitious reactions to occur. A potential advantage of hydrated lime may be that calcium ions and hydroxide ions are supplied in the same molecule. In another example, the calcium source may be Ca(NO₃)₂ or CaCl₂ with the hydroxide being supplied form NaOH or KOH, for example. One of ordinary skill would understand the alternate calcium source and hydroxide source may be included in a cement composition in the same way as hydrated lime. For example, the calcium source and hydroxide source may be included in a silica source-to-hydrated-lime weight ratio of about 10:1 to about 1:1 or a ratio of about 3:1 to about 5:1. Where present, the alternate calcium source and hydroxide source may be included in the cement compositions in an amount in the range of from about 10% to about 100% by weight of the silica source, for example. In some examples, the alternate calcium source and hydroxide source may be present in an amount ranging between any of and/or including any of about 10%, about 20%, about 40%, about 60%, about 80%, or about 100% by weight of the silica source. One of ordinary skill in the art, with the benefit of this disclosure, should recognize the appropriate amount of alternate calcium source and hydroxide source to include for a chosen application.

A target silica lime ratio may be defined and a cement additive comprising two or more cement components may be identified that meets the silica lime ratio. In some examples, the target silica lime ratio may range from about 80/20 silica to free lime by weight to about 60/40 silica to free lime by weight, for example, be about 80/20 silica to free lime by weight, about 70/30 silica to free lime by weight, or about 60/40 silica to free lime by weight. The silica lime ratio may be determined by measuring the available silica and lime for a given cement component.

Other additives suitable for use in cementing operations also may be included in embodiments of the cement compositions. Examples of such additives include, but are not limited to: weighting agents, retarders, accelerators, activators, gas control additives, lightweight additives, gas-generating additives, mechanical-property-enhancing additives, lost-circulation materials, filtration-control additives, fluid-loss-control additives, defoaming agents, foaming agents, transition time modifiers, dispersants, thixotropic additives, suspending agents, and combinations thereof. One of ordinary skill in the art, with the benefit of this disclosure, should be able to select an appropriate additive for a particular application.

As mentioned previously, in order to determine if two or more of the aforementioned cement components are compatible, several lab tests may be run. Additionally, any potential synergistic effects of the cement component may not be known unless several laboratory tests are performed. Typically, a known cement composition may be first formulated and tested for properties such as, for example, the 24 hour compressive strength, fluid loss, and thickening time. Then, varying amounts of additives may be added to a fresh batch of cement compositions and the tests are re-run. The results are gathered form each test and compared. A new set of tests may then be run with new concentrations of additives, for example, to adjust properties of the cement composition. The process of testing various additives in varying concentrations may go on for several trials until an acceptable cement composition or compositions is formulated. An acceptable cement composition may be one that meets certain design requirements, such as compressive strength, fluid loss, and thickening time. The cement composition design process may be done in a heuristic manner leading to a cement composition that may have the required engineering properties but may not be optimized for cost. Additionally, silica sources such as, for example, CKD, have been previously used as either pure fillers or in some examples, reactive components, in Portland based cement compositions. CKD will contribute a portion of silica which requires a portion of lime to react. In methods of cement composition formulation described above, the heuristic process does not take into account the silica to lime ratio of a composition.

The method described herein may reduce or eliminate the heuristic search for by a process that identifies a cement additive through a process of measuring and categorizing a variety of cement components referred to as reactivity mapping. Reactivity mapping may generate a correlation between properties of inorganic particles. Reactivity mapping may comprise several steps. One step may comprise measuring the physical and chemical properties of different materials through standardized tests. Another step may comprise categorizing the materials through analysis of data collected and the predicted effect on cement slurry properties. Yet another step may comprise utilizing the data to estimate material reactivity, improve cement performance, predicting blend mechanical properties mathematically based on analytical results, and/or predict slurry density dependence of compressive strength.

Measuring physical and chemical properties of each selected cement component may comprise many laboratory techniques and procedures including, but not limited to, microscopy, spectroscopy, x-ray diffraction, x-ray fluorescence, particle size analysis, water requirement analysis, scanning electron microscopy, energy-dispersive X-ray spectroscopy, surface area, specific gravity analysis, thermogravimetric analysis, morphology analysis, infrared spectroscopy, ultraviolet-visible spectroscopy, mass spectroscopy, secondary ion mass spectrometry, electron energy mass spectrometry, dispersive x-ray spectroscopy, auger electron spectroscopy, inductively coupled plasma analysis, thermal ionization mass spectroscopy, glow discharge mass spectroscopy x-ray photoelectron spectroscopy, mechanical property testing, Young's Modulus testing, rheological properties, Poisson's Ratio. One or more of the preceding tests may be consider API tests, as set forth in the API recommended practice for testing well cements (published as ANSI/API recommended practice 10B-2). Additional API tests not specifically listed above may also be used for the measurements. The physical and chemical properties may be measured for a group of cement components. Two or more of the cement components measured may be different types of cement components (e.g., volcanic rock, CKD, fly ash, etc.). Two or more of the cement components may be the same type but from different sources (e.g., volcanic rock from source 1, volcanic rock from source 2, etc.).

X-ray powder diffraction is one analysis technique that may be used for measuring the physical and chemical properties of the cement components. X-ray powder diffraction is a technique of exposing a sample to x-rays, neutrons, or electrons and measuring the amount of inter-atomic-diffraction. The sample acts a diffraction grating thereby producing a differing signal at different angles. The typical properties that may be measured are the phase identification for the identification and characterization of a crystalline solid. Other properties may be crystallinity, lattice parameters, expansion tensors, bulk modulus, and phase transitions.

X-ray fluorescence is another analysis technique that may be used for measuring the physical and chemical properties of the cement components. X-ray fluorescence may use short wave x-rays to ionize atoms in a sample thereby causing them to fluoresce at certain characteristic wavelengths. The characteristic radiation released by a sample may allow accurate identification of the component atoms in the sample as well as their relative amounts.

Particle size analysis is another analysis technique that may be used for measuring the physical and chemical properties of the cement components. Particle size analysis may be accomplished through analysis by various laboratory techniques including but not limited to laser diffraction, dynamic light scattering, static image analysis, and dynamic image analysis. Particle size analysis may also provide information about the morphology of a particular sample. Morphology may include parameters such as sphericity and roundness as well as the general shape of a particle such as disk, spheroid, blade, or roller. With a knowledge of the morphology and particle size, the average surface area and volume may be estimated. Surface area and volume may be important in determining the water requirement as well as reactivity. In general, a relatively smaller particle size may react more quickly than a relatively larger particle size. Also the relatively smaller particle size may have a greater water requirement to completely hydrate than a relatively larger particle size.

Energy dispersive x-ray spectroscopy is another analysis technique that may be used for measuring the physical and chemical properties of the cement components. Energy dispersive x-ray spectroscopy is an analytical technique used to analyze the elements present in a sample and determine the chemical characterization of a sample. Other techniques may include Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, mass spectroscopy, secondary ion mass spectrometry, electron energy mass spectrometry, dispersive x-ray spectroscopy, auger electron spectroscopy, inductively coupled plasma mass spectrometry (ICP-MS), thermal ionization mass spectroscopy, glow discharge mass spectroscopy, and x-ray photoelectron spectroscopy.

The cement components may be analyzed to determine their water requirement. Water requirement is typically defined as the amount of mixing water that is required to be added to a powdered, solid material to form a slurry of a specified consistency. Water requirement for a particular cement component may be determined by a process that includes a) preparing a Waring blender with a specified amount of water, b) agitating the water at a specified blender rpm, c) adding the powdered solid that is being investigated to the water until a specified consistency is obtained, and d) calculating the water requirement based on the ratio of water to solids required to reach the desired consistency.

The cement components may be analyzed to determine their specific surface area. Specific surface area generally refers to the total surface area and may be reported as the total surface area per unit mass. Values obtained for specific area are dependent on the analysis technique. Any suitable analysis technique may be used, including, without limitation adsorption, adsorption based methods such as Brunauer-Emmett-Teller (BET) analysis, methylene blue staining, ethylene glycol monoethyl ether adsorption, and a protein-retention method, among other.

Thermogravimetric analysis is another analysis technique that may be used for measuring the physical and chemical properties of the cement components. Thermogravimetric analysis is a method of thermal analysis wherein changes in physical and chemical properties of a sample may be measured. In general the properties may be measured as a function of increasing temperature, such as with a constant heating rate, or as a function of time with a constant temperature or a constant mass change. Properties determined by thermogravimetric analysis may include first-order phase transitions and second-order phase transitions such as vaporization, sublimation, adsorption, desorption, absorption, chemisorption, desolvation, dehydration, decomposition, oxidation and reduction reactions, ferromagnetic transition, superconducting transition, and others.

In addition to determining physical and chemical properties of the cement components themselves, laboratory tests may also be run to determine behavior of the cement components in a cement composition. For example, the cement components may be analyzed in a cement composition to determine their compressive strength development and mechanical properties. For example, a preselected amount of the cement component may be combined with water and lime (if needed for setting). The mechanical properties of the cement composition may then be determined including, compressive strength, tensile strength, and Young's modulus. Any of a variety of different conditions may be used for the testing so long as the conditions are consistent for the different cement components.

Compressive strength is generally the capacity of a material or structure to withstand axially directed pushing forces. The compressive strength of the cement component may be measured at a specified time after the cement component has been mixed with water and the resultant cement composition is maintained under specified temperature and pressure conditions. For example, compressive strength can be measured at a time in the range of about 24 to about 48 hours (or longer) after the fluid is mixed and the fluid is maintained at a temperature of from 100° F. (37.77° C.) to about 200° F. (93.33° C.) and atmospheric pressure. Compressive strength can be measured by either a destructive method or non-destructive method. The destructive method physically tests the strength of treatment fluid samples at various points in time by crushing the samples in a compression-testing machine. The compressive strength is calculated from the failure load divided by the cross-sectional area resisting the load and is reported in units of pound-force per square inch (psi). Non-destructive methods typically may employ an Ultrasonic Cement Analyzer (“UCA”), available from Fann® Instrument Company, Houston, Tex. Compressive strengths may be determined in accordance with API RP 10B-2, Recommended Practice for Testing Well Cements, First Edition, July 2005.

Tensile strength is generally the capacity of a material to withstand loads tending to elongate, as opposed to compressive strength. The tensile strength of the cement component may be measured at a specified time after the cement component has been mixed with water and the resultant cement composition is maintained under specified temperature and pressure conditions. For example, tensile strength can be measured at a time in the range of about 24 to about 48 hours (or longer) after the fluid is mixed and the fluid is maintained at a temperature of from 100° F. (37.77° C.) to about 200° F. (93.33° C.) and atmospheric pressure. Tensile strength may be measured using any suitable method, including, without limitation, in accordance with the procedure described in ASTM C307. That is, specimens may be prepared in briquette molds having the appearance of dog biscuits with a one square inch cross-sectional area at the middle. Tension may then be applied at the enlarged ends of the specimens until the specimens break at the center area. The tension in pounds per square inch at which the specimen breaks is the tensile strength of the material tested.

Young's modulus also referred to as the modulus of elasticity is a measure of the relationship of an applied stress to the resultant strain. In general, a highly deformable (plastic) material will exhibit a lower modulus when the confined stress is increased. Thus, the Young's modulus is an elastic constant that demonstrates the ability of the tested material to withstand applied loads. A number of different laboratory techniques may be used to measure the Young's modulus of a treatment fluid comprising a cementitious component after the treatment fluid has been allowed to set for a period of time at specified temperature and pressure conditions.

Although only some select laboratory techniques may have been mentioned, it should be understood that there may be many analytical techniques that may be appropriate or not appropriate for a certain sample. One of ordinary skill in the art with the benefit of this disclosure should be able to select an appropriate analytical technique to determine a certain property of interest.

Once the analytical techniques have been performed on the cement components, the data may be categorized and correlated. Some categories may include, but are not limited to, specific surface area, morphology, specific gravity, water requirement, etc. In some examples, the components may be categorized by relative amounts, including amount of at least one of the following: silica, alumina, iron, iron, calcium, calcium, sodium, potassium, magnesium, sulfur, oxides thereof, and combinations thereof. For example, the components may be categorized based on an oxide analysis that includes without limitation, silica content, calcium oxide content, and alumina content among other oxides that may be present in the cement component. In addition, correlations between the cement components may be generated based on the data or categorization of the data. Additionally, correlations may be defined or generated between properties of the cement components based on the data. For example, the various categories of properties may be plotted against one another. In some examples, water requirement versus specific surface area may be plotted. Accordingly, the water requirement of the cement component may be correlated to the specific surface area so that the specific surface area is a function of water requirement. Specific surface area may be used to predict reactivity of a cement component (or components). However, specific surface area may not always be available for each material as specific surface area analysis typically requires a specialized instrument. Accordingly, if the water requirement may be obtained for the cement component, the correlation between water requirement and specific surface area may be used to obtain an estimate for specific surface area, which may then be used to predict reactivity. In addition to correlations between specific surface area and reactivity, correlations may also be made between specific surface area and other mechanical properties such as tensile strength and Young's modulus.

Some cement components that are alkali soluble may comprise reclaimed or natural materials. Specifically silica containing cement components may comprise materials such as mined materials, for example volcanic rock, perlite, waste materials, such as fly ash and CKD, and agricultural ashes as previously described. In some examples the cement component that is alkali soluble may have synergistic effects with a Portland cement while others may be incompatible. In some examples a cement component that is alkali soluble may cause gelation, high heat generation, water retention, among other effects. These and other effects may be realized during laboratory testing of the cement component in a cement composition comprising Portland cement. Laboratory equipment may be configured to detect the effects of the cement component on the composition. In some examples, equipment such a calorimeter may measure and quantify the amount of heat generation per unit mass of the cement component. Viscometers may measure the increase in gelation caused by the cement component. Each of the physical effects caused by the addition of the cement component may be measured at several concentrations and then categorized, e.g., plotted or mapped. Once a component is mapped, the effect of adding the component to a cement composition may be predicted by referencing the categorization.

As mentioned previously, some cement components that are alkali soluble may induce gelling when included in a cement composition. Although a higher gelling rate may be undesirable in some examples, in other examples, a higher gelling rate may be advantageous or necessary to meet the engineering design criteria. Usually one of ordinary skill in the art would select a suitable gelling agent or viscosifier for use in the cement composition. With the benefit of mapping, one of ordinary skill should be able to select a cement component that is alkali soluble that may serve a dual purpose. For example, a cement component may increase the compressive strength of a cement composition but also increase the gelling during mixing. If the engineering design criteria require a higher gelling during mixing, it may be advantageous to include the cement component that increases the compressive strength while also increasing gelling. The inclusion of a cement component that exhibits multiple effects may reduce the amount of additional additives, such as gelling agents or viscosifiers, needed, which may be high cost. Since the component's gelling effect may have been documented in a map, the amount of component to include in a cement composition may be readily determined.

Another potentially advantageous physical effect that may be characterized is dispersing ability. Some cement components may comprise relatively spherical particles. The relatively spherical particles may exert a “roller bearing” effect in a cement composition with water. The effect may cause the other components in the cement composition to become more mobile thereby dispersing the components in the cement composition. If particles that are roughly 1/7^(th) or smaller than the primary component in a slurry, then the apparent viscosity may decrease. Another potentially advantageous physical property that may be mapped is surface area. Surface area may relate to density wherein a relatively higher surface area particle may lower the density of a cement composition. Particles which lower the density may be used as a low density additive. Another potentially advantageous effect that may be mapped is particle size. Components with relatively smaller particle sizes may have the ability to form a filter cake against a formation thereby blocking cement slurry from escaping into a formation. Cement components with a small particle size may be used as a fluid loss control agent. With the benefit of the present disclosure, one of ordinary skill should be able to select a cement component and map its properties. One of ordinary skill should also be able to select a secondary property of interest of the cement component and with the benefit of the map, create a slurry with the desired properties.

Another potential benefit of replacing traditional cement additives with silica based cement components is a reduction in cost. A silica based cement component may partially or fully replace a relatively more expensive cement additive as discussed above. The cost of the cement composition may be improved by balancing the required engineering parameters such as compressive strength, mixability, free water content, and others in order to maximize the amount of relatively lower cost silica based cement components. Any remaining deviation from the engineering requirement may be “made up” with the relatively more expensive cement additive. In this way, the cement composition may be reduced to a minimum cost per pound since the engineering requirements are met with a blend of primarily lower cost components.

Once the data is collected by the chosen laboratory techniques, categorized, and mapped, several operations may be performed on the data in order to yield predictions about a cement composition that comprises mapped cement components. Set properties, for example, may be estimated. A method of estimating the material reactivity based on the reactive index will be described below. Material reactivity may be based on many parameters such as specific surface area and specific gravity, among others. Another use for the mapped data may be to increase cement slurry performance based on parameters such as particle shape, particle size, and particle reactivity. The data may also be used to predict and capture slurry density dependence of compressive strength and use the insight gathered to design improved cement formulations. The data may also be used to predict a slurry composition to achieve an improved cement formulation. The criteria for just right may be compressive strength, cost, rheology, mechanical properties, fluid loss control properties, thickening times, and others.

Reactivity mapping may be used to estimate various mechanical properties of a cement component, including compressive strength, tensile strength, and Young's modulus. As previously described, correlations may be made between specific surface area and certain mechanical properties, such as reactivity, tensile strength, and Young's modulus. Using these correlations the mechanical properties for a cement component or combination of cement components may be predicted.

One technique that may be used to correlate reactivity and specific surface area is the reactive index. Without being limited by theory, the reactive index of a cement component may be referred to as a measure of the cement component's reactivity as adjusted for differences in surface area. It is important to note that the term “cement component” refers to any material that is cementitious when mixed with water and/or lime and a suspending agent, when necessary, such that the slurry is stable. A “cementitious reactive index” CRI_(i) can be defined as, but not limited to, Equation 1 as follows:

CRI_(i) =f _(CRI)(CS_(i),ρ_(i),SSA_(PSDi),)  [1]

-   -   Where:     -   CS_(i)=Unconfined UCS (ultimate compressive strength) obtained         from samples cured at specific reference temperature, pressure         and age.     -   ρ_(i)=Density of slurry that was prepared and cured for         measuring UCS SSA_(PSDi)=Specific surface area obtained by         typical particle size analysis methods.         A “physicochemical index” (PCI) of the cementitious component         may be defined as, but not limited to Equation 2:

PCI_(i) =f _(PCI)(SA_(i),SG_(i) ,D ₅₀ ,C _(Si) ,C _(Ca) ,C _(Al) ,C _(Na) ,C _(Fe) ,C _(other species))  [2]

-   -   Where:     -   SA_(i)=Surface area of the cementitious component i,     -   SG_(i)=specific gravity of the cementitious component i,     -   D₅₀=mass average or volume average diameter of the particle size         distribution of cementitious component i,     -   C_(Si)=Mass concentration of silica oxide of component i,     -   C_(Ca)=Mass concentration of calcium oxide of component i,     -   C_(Al)=Mass concentration of Aluminum oxide of component i,     -   C_(Na)=Mass concentration of sodium oxide of component i,     -   C_(Fe)=Mass concentration of iron oxide of component i,

It should be noted that the mass concentrations referenced above and here to for, may be measured, but is not limited to X-ray fluorescence spectroscopy measuring technique and a reference to “component i” is equivalent to “cementitious component i”. The functions in Equations 1 and 2 that define CRI_(i) and PCI_(i), when properly defined, the following universal relationship may hold for a wide range of cementitious materials such as, but not limited to, Portland cements; fly ash; other pozzolanic materials; other ashes; etc.

CRI_(i) =f _(CRI-PCI)(PCI_(i))  [3]

FIG. 1 is a graph of Equation 1 versus Equation 2, for real data, illustrating the accuracy of Equations 1, 2 and 3 when applied to five different types of cementitious material sources and three samples of similar materials but from different sources. The simulated data was found to have a relationship of y=36.252x^(0.2256,) wherein R²=0.9406.

In some examples, the form of Equation 3 may be a power law, such as in Equation 4.

CRI_(i) =A{PCI_(i)}^(B)  [4]

A and B are coefficients that may be unique the various species and sources of cementitious materials selected. Once the generalized function defined in Equation 4 is defined for a given population or group of cementitious components, a linear or nonlinear summation relationship further defined below, may be used in conjunction with Equation 5 to predict the UCS of various combinations of cementitious materials for specified slurry densities, temperatures, pressures and curing age.

CRI_(c) =A{PCI_(c)}^(B)  [5]

-   -   Where,     -   CRI_(c) is defined as the CRI for the unique combination of n         cementitious components as the composite, and similarly     -   PCI_(c) is defined as the Physicochemical Index for the         composite.         A given composite with mass of m_(c) is defined as:

m _(c) =f _(i) +f _(i+1) +f _(i+2) + . . . +f _(n)  [6]

Where: f_(i) is defined as the mass fraction of the cementitious component i, and n is the total number of independent cementitious components. Once the function is defined in Equation 5, then the composite value of the physicochemical reactive index may be computed using Equation 7 as follows:

PCI_(c) =f ₁PCI₁ +f ₂PCI₂ +f ₃PCI₃ + . . . +f _(n)PCI_(n)  [7]

Where: PCI_(c) is defined as the overall chemical reactive index for a blend of n number of uniquely independent cementitious components, f_(i) is defined as the mass fraction of the cementitious component i, and n is the total number of independent cementitious components. Once PCI_(c) has been determined for specific assumed blend of selected cementitious components, then the linear or non-linear summations (Equations 8 and 9) are determined for the following terms:

ρ_(c) =f ₁ρ₁ +f ₂ρ₂ +f ₃ρ₃ + . . . +f _(n)ρ_(n)  [8]

and,

SSA_(PSDc) =f ₁SSA_(PSD1) +f ₂SSA_(PSD2) +f ₃SSA_(PSD3) + . . . +f _(n)SSA_(PSDn)  [9]

PCI_(c) is used to compute the value of CRI_(c) using either Equation 5 or the more generalized form of Equation 3 for the composite terms. Once CRI_(c) is determined for the given composite blend, then the composite values of ρ_(c) and SSA_(PSDc) may be used along with Equation 10 to predict the actual compressive strength of the composite blend, CS_(c).

CRI_(c) =f _(CRI)(CS_(c),ρ_(c),SSA_(PSDc),density of slurry)  [10]

Experimental data was collected for specific composite blends and is summarized in the table below:

TABLE 1 Mass Fractions of Cementitious Components Cementitious Composite Composite Composite Component Blend 1 Blend 2 Blend 3 A 0.36 0.53 B 0.32 C 0.32 0.31 D 0.33 E 0.32 F 0.35 G 0.16 Totals 1.00 1.00 1.00 It is important to note that each of the cementitious components above were either distinctly different species (type) of cementitious composition and/or from a different source.

FIG. 2 is another plot of Equation 1 versus Equation 2 for real data, showing the accuracy of Equations 1, 2, and 3. Equations 1 through 10 may also be used for predicting other mechanical properties, including but not limited to, Young's Modulus of Elasticity and Tensile Strength. Additionally, it should be noted that even though a “linear summation” technique is presented in the previous development, that this invention also includes other methods such as the non-linear summation method presented in Equation 11.

PCI_(c)=(1+f ₁)^(a1)PCI₁+(1+f ₂)^(a2)PCI₂+(1+f ₃)^(a3)PCI₃+ . . . +(1+f _(n))^(an)PCI_(n)  [11]

Where: ai are exponents that are determined for a unique set of cementitious components.

Further examples using the chemical reactive index, water requirement and other analytical parameters will now be discussed. A statistical table may be generated that plots chemical reactive index against water requirement. An example is shown in Table 2.

TABLE 2 Chemical Reactive Index Vs. Water Requirement Water High X1 X4, X5 X8 Requirement Medium X2 X6 X9, X10 Low X3 X7 X11 . . . Xn Low Medium High Reactive Index

Other analytical parameters such as particle size versus chemical reactive index, heat generation versus chemical reactive index, and others may also be used. By ranking the chemical reactive index against an analytical parameter, a blend of components may be selected that has a minimized cost and an improved chemical reactive index while still having a mixable composition. In some examples, a selected cement composition may have too much free water to set properly. In such examples, a component having a high water requirement may be selected to replace a component in the cement composition or supplement the cement composition. The selected component having the high water requirement may be selected based on the chemical reactive index to ensure that the overall blend has sufficient reactivity. A cement composition comprising the selected cement component may exhibit less free water due to the high water requirement of the component and may also exhibit the same reactivity from selecting the appropriate chemical reactive index. The reactivity of a cement composition may be tuned based on the selection of cement component having the desired reactivity. A component having a high reactivity may exhibit a faster set time than one with a low reactivity.

The reactivity of a cement composition may be affected by wellbore temperature. If a wellbore has a relatively low temperature, about <150° F. or less, a component having a relatively higher reactivity may be required to ensure that the cement composition develops adequate strength. In previous cement compositions, a chemical accelerator may have been used to enhance the reaction speed in a relatively lower temperature well. A cement composition comprising a relatively higher chemical reactive index component may not require an accelerator due to the high reactivity of the component. Cement compositions comprising a high reactivity component may not require an accelerator and therefore may have a lower overall cost. If a wellbore has a relatively high temperature, about >150° F. or greater, the cement component may be selected to have a relatively lower reactivity. Selecting a lower reactivity may be advantageous when the high temperature of a wellbore may cause the cement composition to set too quickly. In previous cement compositions, a cement set retarder may have been used to reduce the reaction speed in a relatively higher temperature well. By selecting a relatively lower reactivity component, the cement set reaction may potentially be slowed without the use of a retarder. Selecting an appropriate cement component based on reactivity may reduce the cost of the cement composition by eliminating or reducing the need for accelerators and retarders. Furthermore, a combination of cement components may be blended to control the reactivity, for example by adding low, medium, and high reactivity cement components, a cement composition may be created that has a controlled reactivity along the spectrum of wellbore temperatures. One of ordinary skill in the art, with the benefit of this disclosure, should recognize the appropriate amount and type of cement component to include for a chosen application.

Another application of the previously mention statistical correlation may be in classifying cement components by cost among other factors. In general, the reactivity of a cement composition may be maximized to ensure that the cement composition will attain enough compressive strength to meet the design requirement of a particular well. If a specific cement composition far exceeds the engineering requirements, then an alternate cement composition comprising potentially less expensive components may be formulated. The following equations illustrate an improvement scheme for a cement composition.

$\begin{matrix} {{CRI},{{composite} = {\sum\left( {{CRI}_{i}*\% \mspace{14mu} {Concentration}} \right)}}} & \lbrack 12\rbrack \\ {{{Cost}\mspace{14mu} {Index}},{{composite} = {\sum\left( {{Cost}_{i}*\% \mspace{14mu} {Concentration}} \right)}}} & \lbrack 13\rbrack \\ {\left. {{Optimized}\mspace{14mu} {Blend}}\rightarrow{\max \mspace{14mu} {CRI}} \right.,{{composite}\; \Lambda \; \min \mspace{14mu} {Cost}\mspace{14mu} {Index}},{composite}} & \lbrack 14\rbrack \\ {{{Optimization}\mspace{14mu} {Ratio}} = {\max \left\lbrack \frac{{CRi},{composite}}{{{Cost}\mspace{14mu} {Index}},{composite}} \right\rbrack}} & \lbrack 15\rbrack \\ {{{{Constraints}\text{:}\mspace{14mu} {Cost}\mspace{14mu} {Index}} < {\$ \; C}},{{{where}\mspace{14mu} C} \geq 0}} & \; \\ {{{CS} = \left. {f\left( {{CRI},{{analytical}\mspace{14mu} {properies}}} \right)}\rightarrow{CS} \right.},{\min < {CS}},{{composite} < {CS}},\max} & \; \end{matrix}$

Using all the techniques previously discussed, a cement composition having a minimized cost and a maximized reactivity may be calculated. A first step may be to identify the engineering requirements of a particular well. Another step may be to define the inventory available at a particular field camp or well site. As previously mentioned, a particular region may have access to only a certain amount or kind of cement components. Some of the factors that may be considered in addition to those previously mentioned are the cost of goods sold, bulk density, and specific gravity for the available and potential inventory. The available cement components may be tested in a laboratory and classified using the methods previously discussed. Analytical study may comprise the various analytical techniques previously mentioned along with the physiochemical reactivity measurements for compressive strength, young's modulus, water requirement, and others. Next the correlations between the mechanical performance measures and analytical properties may be calculated. The chemical reactive index may also be calculated. A statistical table of the chemical reactive index and the water requirement may be calculated along with the chemical reactive index versus other selected analytical parameters.

An initial virtual design may be selected and tested to see if it meets the functional requirements defined by the engineering parameters. The initial virtual design may be based on a previous design, chosen from field experience, or selected by a computer. The virtual design may be based on, among other factors, the chemical reactivity of the cement components. If the virtual design meets all of the engineering parameters, a cost index for the composition may be calculated. The components of the cement composition may be adjusted iteratively until a cement composition having the maximum reactive index and minimized cost is achieved. In some examples, a fluid loss control additive, thickening additive, or other cement additives may be necessary to meet the functional requirements. As was previously described, the amount of cement additives that may need to be added to a cement composition may be minimized by selecting cement components that have inherent properties such as high reactive index, low water requirement, fluid loss control properties, and dispersive properties, among others.

A relationship between Young's modulus and compressive strength may be expressed as in Equation 16.

Y=A _(ym) *f(ρ)*g(CS)  [16]

Where f and g are functions that use density and compressive strength as inputs. A more specific form of this relationship may be expressed in Equation 17 as follows:

YM=A _(ym)(ρ)^(Bden)(CS)^(Bcs)  [17]

Where:

A_(YM), Bden, Bcs are constants for a given family of cementitious formulations

ρ=density

CS=compressive strength

YM=Young's modulus

Equation 16 can also be written to determine the compressive strength.

$\begin{matrix} {{CS} = \left\{ {\left\lbrack \frac{Y{M\left( {psi} \right)}}{A_{ym}} \right\rbrack \left\lbrack \frac{1}{\rho^{Bden}} \right\rbrack} \right\}^{1/{Bcs}}} & \lbrack 18\rbrack \end{matrix}$

Each of density, compressive strength, and Young's modulus may have any units appropriate for a particular application. For example, the units of density may be units of lbm/gal, kg/m³, or any other appropriate units. Compressive strength may have units of psi, pascal, or any other appropriate units. Young's modulus may have units of psi, pascal, or any other appropriate units.

The constants of Equations 16 and 17 may be determined for a particular blend or system of cementitious components. A cement system may be defined as the base ingredients that are required to form a cementitious mixture that can set to form a hardened mass when combined with water. Each system may have a particular set of constants for Equation 16. For example, a cement composition comprising class H Portland cement, class C fly ash, and pumice may have differing constants than a cement composition comprising pumice, hydrated lime, metakaolin, and class C fly ash. As previously discussed, Young's modulus may be modulated by changing a concentration of one or more of the cementitious components. Constants of Equation 16 may be determined by preparing a plurality of cement composition with varying concentrations of each ingredient and testing the Young's modulus of each resulting set composition. Young's modulus may be plotted and a regression analysis may be performed to find the constants of Equations 16 and 17. For Equation 17, at least three cement compositions must be prepared as there are three degrees of freedom to determine the three constants in Equation 17.

A cement for use in a wellbore may have a particular Young's modulus and density requirement provided by a customer, regulations, determined by best practices, determined by previously completed cement jobs, or any other means. A particular cement system may be chosen for a variety of reasons including, but not limited to, formation compatibility and compressive strength requirement. Constants for Equation 17 may be known for the selected cement system and in conjunction with density and Young's modulus requirements, Equation 18 may be used to determine an initial compressive strength value. The previously discussed design process for a slurry using reactive index or any other method may be applied to generate a first cement composition. The first composition may be tested for a first compressive strength and first Young's modulus. A second and third composition may be generated wherein the second and third compositions have compressive strengths greater and less than the first compressive strength.

Each of the first, second, and third compressive strengths and Young's modulus may be plotted and Equation 18 may be fit to the plotted data using regression analysis to determine new quantitative values for constants Aym, Bden, and Bcs. The quantitative values for the constants may allow for greater precision in calculating the required Young's modulus for a particular compressive strength target.

Once quantitative values for the constants is known, Equation 18 may be used with the Young's modulus and density requirement to compute a revised compressive strength that may result from the Young's modulus input. The previously discussed slurry design process may be used with the new computed compressive strength to design a cement composition that meets the compressive strength requirements. The designed slurry may then be tested for compressive strength and Young's modulus to confirm the composition meets or exceeds the design requirements.

Although described herein in terms of Equations 16-18, one of ordinary skill in the art will appreciate that there may be other functions that may be used to correlate Young's modulus and compressive strength.

Rearranging Equation 10 results in Equation 19, that can be used to compute a correlation between the mass ratio of water to cementitious material (w/c) in a cement slurry (Abram's law).

CS_(c) =f _(CSc)(CRI_(c),ρ_(c),SSA_(PSDc),density of slurry)  [19]

Equation 18 and Equation 16 may be combined to form Equation 20 where Young's modulus is expressed in terms of density for a given cement dry blend.

YM=A _(ym)(ρ)^(Bden)(CS_(c))^(Bcs)  [20]

An alternate method of modeling Young's modulus may be from a correlation with slurry composition, curing temperature, and density. Equation 21 illustrates an example of a model where (cement blend composition) may be a complex function with dependence on physio-chemical properties of the constituent species in the composition, g(T) may be, but not necessarily limited, to an Arrhenius function, and r(Density) may be but not limited to a power-law or an exponential. A complex function may include properties such as particle size, surface area, water requirement, silica, calcium oxide, alumina, iron oxide, C2S, C3S, C3AF, and silicate content.

YM=f[(cement blend composition)*g(T)*r(Density)]  [21]

It will be appreciated by those of ordinary skill in the art, the cement compositions disclosed herein may be used in a variety of subterranean applications, including primary and remedial cementing. The cement compositions may be introduced into a subterranean formation and allowed to set. As used herein, introducing the cement composition into a subterranean formation includes introduction into any portion of the subterranean formation, into near wellbore region surrounding the wellbore, or into both. In primary cementing applications, for example, the cement compositions may be introduced into the annular space between a conduit located in a wellbore and the walls of the wellbore (and/or a larger conduit in the wellbore), wherein the wellbore penetrates the subterranean formation. The cement composition may be allowed to set in the annular space to form an annular sheath of hardened cement. The cement composition may form a barrier that prevents the migration of fluids in the wellbore. The cement composition may also, for example, support the conduit in the wellbore. In remedial cementing applications, the cement compositions may be used, for example, in squeeze cementing operations or in the placement of cement plugs. By way of example, the cement compositions may be placed in a wellbore to plug an opening (e.g., a void or crack) in the formation, in a gravel pack, in the conduit, in the cement sheath, and/or between the cement sheath and the conduit (e.g., a microannulus).

While the present description refers to cement compositions and cement components, it should be understood that the techniques disclosed herein may be used with any suitable wellbore treatment composition and corresponding solid particulates of which cement compositions and cement components are one example. Additional examples of slurry compositions may include spacer fluids, drilling fluids, cleanup pills, lost circulation pills, and fracturing fluids, among others. Suitable solid particulates may include any of a variety of inorganic particles commonly used in well treatments

Accordingly, this disclosure describes systems, compositions, and methods relating to slurry design process. Without limitation, the systems, compositions and methods may further be characterized by one or more of the following statements:

Statement 1. A method of generating a wellbore treatment fluid comprising: obtaining a target Young's modulus; calculating a compressive strength requirement from a correlation comprising compressive strength and Young's modulus using the target Young's modulus as an input; classifying a plurality of solid particulates using correlations; calculating a reactive index and/or a water requirement for at least one of the solid particulates; and selecting two or more solid particulates from the plurality of solid particulates to create a wellbore treatment fluid, wherein two or more solid particulates are selected such that when the wellbore treatment fluid is prepared and set, the set wellbore treatment fluid has a 24 hour compressive strength greater than or equal to the compressive strength requirement.

Statement 2. The method of statement 1 wherein the correlation is YM=A_(ym)*f(ρ)*g(CS) where YM is Young's modulus, f(ρ) is a function with density as an input, and g(CS) is a function with compressive strength as an input.

Statement 3. The method of any preceding statement further comprising adjusting one or more concentrations of the selected two or more solid particulates to meet one or more desired parameters.

Statement 4. The method of any preceding statement wherein the one or more desired parameters comprise a cost objective.

Statement 5. The method of any preceding statement wherein the one or more desired parameters comprise at least one parameter selected from the group consisting of compressive strength, fluid loss, mud densities, slurry density, pore pressures, thickening time, tensile strength, Young's Modulus, Poisson's Ratio, rheological properties, slurry stability, fracture gradient, remaining well capacity, transition time, free fluid, gel strength, and combinations thereof.

Statement 6. The method of any preceding statement further comprising analyzing the solid particulates to generate data about physical and chemical properties of the solid particulates and generating correlations between the solid particulates based on the data.

Statement 7. The method of any preceding statement wherein the analyzing the solid particulates comprises analysis by one or more techniques selected from the group consisting of microscopy, spectroscopy, x-ray diffraction, x-ray fluorescence, particle size analysis, water requirement analysis, scanning electron microscopy, energy-dispersive X-ray spectroscopy, surface area, specific gravity analysis, thermogravimetric analysis, morphology analysis, infrared spectroscopy, ultraviolet-visible spectroscopy, mass spectroscopy, secondary ion mass spectrometry, electron energy mass spectrometry, dispersive x-ray spectroscopy, auger electron spectroscopy, inductively coupled plasma analysis, thermal ionization mass spectroscopy, glow discharge mass spectroscopy x-ray photoelectron spectroscopy, mechanical property testing, Young's Modulus testing, rheological properties, Poisson's Ratio, API testing, and combinations thereof.

Statement 8. The method of any preceding statement further comprising generating a statistical table comprising two or more different parameters of the solid particulates.

Statement 9. The method of any preceding statement, wherein the different parameters comprise the water requirement and the reactive index.

Statement 10. The method of any preceding statement, further comprising introducing the wellbore treatment fluid into a well bore.

Statement 11. The method of any preceding statement, wherein the wellbore treatment fluid is introduced into the wellbore using one or more pumps.

Statement 12. The method of any preceding statement, further comprising mixing the components of the wellbore treatment fluid using mixing equipment, the components comprising the two or more solid particulates.

Statement 13. A method of improving a wellbore treatment fluid, the method comprising: calculating a compressive strength requirement using a target Young's modulus as an input in a correlation comprising compressive strength, Young's modulus, and at least one constant; selecting a target reactive index for the wellbore treatment fluid based on the compressive strength requirement; generating a wellbore treatment fluid based on the target reactive index; adjusting the at least one constant from the correlation based on a compressive strength measurement, Young's modulus measurement, or both of the wellbore treatment fluid to generate an updated at least one constant; calculating a second compressive strength requirement using the target Young's modulus as an input in a correlation comprising compressive strength, Young's modulus, and updated at least one constant; selecting a second target reactive index for the wellbore treatment fluid based on the second compressive strength requirement; generating a second wellbore treatment fluid based on the second target reactive index.

Statement 14. The method of statement 13 wherein the correlation is YM=A_(ym)*f(ρ)*g(CS) where YM is Young's modulus, f(ρ) is a function with density as an input, and g(CS) is a function with compressive strength as an input.

Statement 15. The method of statements 13-14 wherein the reactive index is calculated at a bottom hole circulating temperature.

Statement 16. The method of statements 13-15 wherein the second wellbore treatment fluid further comprises at least one additive selected from the group consisting of weighting agents, retarders, accelerators, activators, gas control additives, lightweight additives, gas-generating additives, mechanical-property-enhancing additives, lost-circulation materials, filtration-control additives, fluid-loss-control additives, defoaming agents, foaming agents, transition time modifiers, dispersants, thixotropic additives, suspending agents, and combinations thereof.

Statement 17. The method of statements 13-16 further comprising calculating a cost of the wellbore treatment fluid.

Statement 18. A system for generating a wellbore treatment fluid comprising: a model correlation comprising compressive strength, Young's modulus, and at least one constant; a plurality of solid particulates; and a computer system operable to accept a target Young's modulus input from a user and generate a wellbore treatment fluid using the target Young's modulus input to the model correlation, wherein the wellbore treatment fluid comprises at least two solid particulates selected form the plurality of solid particulates and wherein a concentration of each of the at least two solid particulates is based on a target property.

Statement 19. The system of statement 18 wherein the correlation is YM=A_(ym)*f(ρ)*g(CS) where YM is Young's modulus, f(ρ) is a function with density as an input, and g(CS) is a function with compressive strength as an input.

Statement 20. The system of statements 18-19 wherein the computer system is further operable to improve the wellbore treatment fluid by calculating a reactive index and adjusting a relative amount of each of the solid particulates to meet or exceed the target property.

Statement 21. The system of statements 18-20 further comprising a database, wherein the database comprises the solid particulates, a cost corresponding to each of the solid particulates, a water requirement for each component, and a reactive index for each component.

Statement 22. The system of statements 18-21 wherein the target reactive index is defined by a user or automatically selected by the computer system.

Statement 23. The system of statement 18-22 wherein the computer system is configured to select an additive to include in the wellbore treatment fluid, wherein the additive comprises at least one additive selected from the group consisting of weighting agents, retarders, accelerators, activators, gas control additives, lightweight additives, gas-generating additives, mechanical-property-enhancing additives, lost-circulation materials, filtration-control additives, fluid-loss-control additives, defoaming agents, foaming agents, transition time modifiers, dispersants, thixotropic additives, suspending agents, and combinations thereof.

Statement 24. The system of statements 18-23 wherein the computer system is further operable to select the solid particulates based on a water requirement.

Examples of the methods of using the preceding techniques will now be described in more detail with reference to FIG. 3. A system 300 for analyzing the cement component is illustrated. The system 300 may comprise a cement component sample 305, analytical instrument 310, and computer system 315. Cement component sample 305 may be any cement component of interest. Cement components as previously described may be generally categorized as alkali soluble. The cement component sample may be placed or fed into analytical instrument 310. In some examples, analytical instrument 310 may be configured to automatically feed cement component sample 305 into analytical instrument 310. Analytical instrument 310 may be configured to analyze the physical and chemical properties of cement component sample 305. As previously described, physical and chemical properties may comprise, without limitation, morphology, chemical composition, water requirement, and others. The data generated by analytical instrument 310 may be sent to computer system 315 for processing. Computer system 315 may comprise a processor, memory, internal storage, input and output means, network connectivity means, and/or other components common to computer systems. Computer system 315 may take the data from analytical instrument 310 as input and store it in the storage for later processing. Processing the data may comprise inputting the data into algorithms which compute a result. Processing the data may also comprise organizing the data and mapping the data as previously described. In particular, the computer system may comprise algorithms configured to process the data to generate a predictive model of the physical and chemical behavior of cement component sample 305. Predictive models may be stored in a predictive model database 320 which may be stored locally or on a network. The predictive model database 320 may comprise all previous predictive models generated by the algorithms as well as maps of the generated data as well as the raw data.

Referring now to FIG. 4, a system 400 for generating cement compositions is illustrated. The system 400 may comprise a predictive model database 320 and computer system 410. In some examples, computer system 410 may be the same computer system 315 of FIG. 3. A user input 420 may define engineering parameters such as the required compressive strength of a cement slurry, the bottom hole static temperature of the wellbore, mud densities, pore pressures, total vertical depth, measured depth, the required rheological properties of the slurry, the thickening time of the slurry, cement materials, cement additives, free fluid, permeability, pore pressure, fracture gradient, mud weight, density, gel strength, stability, suspension, remaining well capacity, transition time, acid resistance, salt tolerance, and other parameters. Computer system 410 may be configured to input user input 420 and the predictive models, maps, and data stored in predictive model database 320 into a predictive cement algorithm. The predictive cement algorithm may generate a cement composition or compositions that meet the engineering requirements define by the user input 420. The output 430 of the predictive cement algorithm may contain the relative amounts of each cement component in the generated cement composition as well as the predicted material properties of the cement composition.

For example, if a user selects Portland cement, fly ash, and volcanic rock as the cement materials available the computer system may query predictive model database 320 for the required models, maps, and data corresponding to the cement materials. As previously described, there may be many different parameters such as particle size, regional source of the cement material, among others that may determine which set of data that is retrieved from predictive model database 320. The predictive cement algorithm may be configured to improve the output cement slurry based on one or more parameters such as cost, compressive strength, or any other chosen parameter. In some examples the predictive cement algorithm may optimize on two or more variable. Optimize in this context should not be understood as arriving at a best result but rather that the cement algorithm is configured to iterate on one or more variables. The output of the algorithm in this example may be for example, 30% Portland by weight, 30% volcanic rock by weight, 20% fly ash, and 20% lime, with a 120% excess by weight of water. The generated slurry may conform within a margin of error to the engineering parameters supplied by user input 420. The generated slurry may be added to predictive model database 320 to be used in future calculations.

As previously discussed, the cement components may have secondary effects such as gelling, dispersive properties, heat generation, and other secondary effects previously mentioned in addition to the primary effect of being cementitious when included in a cement composition. The secondary effects may be beneficial as well. For example, if a cement composition requires a thickening agent, instead of using a separate additive to thicken the cement composition, a cement component that gels may be used in the place of another additive. Other secondary effects may also be taken advantage of in a similar manner. The predictive cement algorithm may calculate the secondary effects of each component in the cement slurry and adjust the relative amounts of each component to ensure the target parameters are met. User input 420 may specify, for example, a relatively higher free water requirement for the cement slurry. The predictive cement algorithm may choose to include a cement component that requires less water based on the maps and data to ensure that the free water requirement specified by user input 420 is met.

Reference is now made to FIG. 5, illustrating use of a cement composition 500. Cement composition 500 may comprise any of the components described herein. Cement composition 500 may be designed, for example, using reactivity mapping as described herein. Turning now to FIG. 5, the cement composition 500 may be placed into a subterranean formation 505 in accordance with example systems, methods and cement compositions. As illustrated, a wellbore 510 may be drilled into the subterranean formation 505. While wellbore 510 is shown extending generally vertically into the subterranean formation 505, the principles described herein are also applicable to wellbores that extend at an angle through the subterranean formation 505, such as horizontal and slanted wellbores. As illustrated, the wellbore 510 comprises walls 515. In the illustration, a surface casing 520 has been inserted into the wellbore 510. The surface casing 520 may be cemented to the walls 515 of the wellbore 510 by cement sheath 525. In the illustration, one or more additional conduits (e.g., intermediate casing, production casing, liners, etc.), shown here as casing 530 may also be disposed in the wellbore 510. As illustrated, there is a wellbore annulus 535 formed between the casing 530 and the walls 515 of the wellbore 510 and/or the surface casing 520. One or more centralizers 540 may be attached to the casing 530, for example, to centralize the casing 530 in the wellbore 510 prior to and during the cementing operation.

With continued reference to FIG. 5, the cement composition 500 may be pumped down the interior of the casing 530. The cement composition 500 may be allowed to flow down the interior of the casing 530 through the casing shoe 545 at the bottom of the casing 530 and up around the casing 530 into the wellbore annulus 535. The cement composition 500 may be allowed to set in the wellbore annulus 535, for example, to form a cement sheath that supports and positions the casing 530 in the wellbore 510. While not illustrated, other techniques may also be utilized for introduction of the cement composition 500. By way of example, reverse circulation techniques may be used that include introducing the cement composition 500 into the subterranean formation 505 by way of the wellbore annulus 535 instead of through the casing 530. As it is introduced, the cement composition 500 may displace other fluids 550, such as drilling fluids and/or spacer fluids that may be present in the interior of the casing 530 and/or the wellbore annulus 535. While not illustrated, at least a portion of the displaced fluids 550 may exit the wellbore annulus 535 via a flow line and be deposited, for example, in one or more retention pits. A bottom plug 355 may be introduced into the wellbore 510 ahead of the cement composition 500, for example, to separate the cement composition 500 from the fluids 550 that may be inside the casing 530 prior to cementing. After the bottom plug 555 reaches the landing collar 580, a diaphragm or other suitable device should rupture to allow the cement composition 500 through the bottom plug 555. The bottom plug 555 is shown on the landing collar 580. In the illustration, a top plug 560 may be introduced into the wellbore 510 behind the cement composition 500. The top plug 360 may separate the cement composition 500 from a displacement fluid 565 and also push the cement composition 500 through the bottom plug 555.

The disclosed cement compositions and associated methods may directly or indirectly affect any pumping systems, which representatively includes any conduits, pipelines, trucks, tubulars, and/or pipes which may be coupled to the pump and/or any pumping systems and may be used to fluidically convey the cement compositions downhole, any pumps, compressors, or motors (e.g., topside or downhole) used to drive the cement compositions into motion, any valves or related joints used to regulate the pressure or flow rate of the cement compositions, and any sensors (i.e., pressure, temperature, flow rate, etc.), gauges, and/or combinations thereof, and the like. The cement compositions may also directly or indirectly affect any mixing hoppers and retention pits and their assorted variations.

EXAMPLES Example 1

A Young's modulus test was prepared for 19 cement compositions. Each composition had a density ranging from 9 ppg (pounds per gallon) (1.078 kg/L) to 15.8 ppg (1.893 kg/L) with a curing temperature ranging from 60° F. (15.56° C.) to 238° F. (114.4° C.). Each of the compositions was placed into a cylinder and allowed to cure before being tested in an unconfined compressive strength test to find the Young's modulus of each set composition. The results are illustrated in FIG. 6.

A curve was fit to the data gathered in FIG. 6. It was found that for the particular compositions tested and plotted the following parameters were found for Equation 16.

-   -   Aym=275     -   Bden=1.25     -   Bcs=0.63         Where the final model is YM=275(ρ)^(1.25)(CS)^(0.63). It was         observed that the coefficient of determination (r²) for the         particular data was 0.9344.

Example 2

A second Young Modulus test was prepared for 23 cement compositions. Each composition included at least 2 components selected from class H Portland cement, class C fly ash, and pumice in varying concentrations. Each of the cement compositions had a density ranging from 12 ppg (1.438 kg/L) to 14.5 ppg (1.737 kg/L) with curing temperatures ranging from 100° F. (37.78° C.) to 180° F. (82.2° C.). Each of the compositions was placed into a cylinder and allowed to cure before being tested in an unconfined compressive strength test to find the Young's modulus of each set composition. The results are illustrated in FIG. 7.

A curve was fit to the data gathered in FIG. 7. It was found that for the particular compositions tested and plotted the following parameters were found for Equation 17.

-   -   Aym=56.7     -   Bden=2.09     -   Bcs=0.56         Where the final model is YM=56.7(ρ)^(2.09)(CS)^(0.56). It was         observed that the coefficient of determination (r²) for the         particular data was 0.9621.

It should be understood that the compositions and methods are described in terms of “comprising,” “containing,” or “including” various components or steps, the compositions and methods can also “consist essentially of” or “consist of” the various components and steps. Moreover, the indefinite articles “a” or “an,” as used in the claims, are defined herein to mean one or more than one of the element that it introduces.

For the sake of brevity, only certain ranges are explicitly disclosed herein. However, ranges from any lower limit may be combined with any upper limit to recite a range not explicitly recited, as well as, ranges from any lower limit may be combined with any other lower limit to recite a range not explicitly recited, in the same way, ranges from any upper limit may be combined with any other upper limit to recite a range not explicitly recited. Additionally, whenever a numerical range with a lower limit and an upper limit is disclosed, any number and any included range falling within the range are specifically disclosed. In particular, every range of values (of the form, “from about a to about b,” or, equivalently, “from approximately a to b,” or, equivalently, “from approximately a-b”) disclosed herein is to be understood to set forth every number and range encompassed within the broader range of values even if not explicitly recited. Thus, every point or individual value may serve as its own lower or upper limit combined with any other point or individual value or any other lower or upper limit, to recite a range not explicitly recited.

Therefore, the present disclosure is well adapted to attain the ends and advantages mentioned as well as those that are inherent therein. The particular examples disclosed above are illustrative only, as the present invention may be modified and practiced in different but equivalent manners apparent to those skilled in the art having the benefit of the teachings herein. Although individual examples are discussed, the invention covers all combinations of all those examples. Furthermore, no limitations are intended to the details of construction or design herein shown, other than as described in the claims below. Also, the terms in the claims have their plain, ordinary meaning unless otherwise explicitly and clearly defined by the patentee. It is therefore evident that the particular illustrative examples disclosed above may be altered or modified and all such variations are considered within the scope and spirit of the present invention. If there is any conflict in the usages of a word or term in this specification and one or more patent(s) or other documents that may be incorporated herein by reference, the definitions that are consistent with this specification should be adopted. 

What is claimed is:
 1. A method of generating a wellbore treatment fluid comprising: obtaining a target Young's modulus; calculating a compressive strength requirement from a correlation comprising compressive strength and Young's modulus using the target Young's modulus as an input; classifying a plurality of solid particulates using correlations; calculating a reactive index and/or a water requirement for at least one of the solid particulates; and selecting two or more solid particulates from the plurality of solid particulates to create the wellbore treatment fluid, wherein two or more solid particulates are selected such that when the wellbore treatment fluid is prepared and set, the set wellbore treatment fluid has a 24 hour compressive strength greater than or equal to the compressive strength requirement.
 2. The method of claim 1 wherein the correlation is YM=A_(ym)*f(ρ)*g(CS) where YM is Young's modulus, f(ρ) is a function with density as an input, and g(CS) is a function with compressive strength as an input.
 3. The method of claim 1 further comprising adjusting one or more concentrations of the selected two or more solid particulates to meet one or more desired parameters.
 4. The method of claim 3 wherein the one or more desired parameters comprise a cost objective.
 5. The method of claim 3 wherein the one or more desired parameters comprise at least one parameter selected from the group consisting of compressive strength, fluid loss, mud densities, slurry density, pore pressures, thickening time, tensile strength, Young's Modulus, Poisson's Ratio, rheological properties, slurry stability, fracture gradient, remaining well capacity, transition time, free fluid, gel strength, and combinations thereof.
 6. The method of claim 1 further comprising analyzing the solid particulates to generate data about physical and chemical properties of the solid particulates and generating correlations between the solid particulates based on the data.
 7. The method of claim 6 wherein the analyzing the solid particulates comprises analysis by one or more techniques selected from the group consisting of microscopy, spectroscopy, x-ray diffraction, x-ray fluorescence, particle size analysis, water requirement analysis, scanning electron microscopy, energy-dispersive X-ray spectroscopy, surface area, specific gravity analysis, thermogravimetric analysis, morphology analysis, infrared spectroscopy, ultraviolet-visible spectroscopy, mass spectroscopy, secondary ion mass spectrometry, electron energy mass spectrometry, dispersive x-ray spectroscopy, auger electron spectroscopy, inductively coupled plasma analysis, thermal ionization mass spectroscopy, glow discharge mass spectroscopy x-ray photoelectron spectroscopy, mechanical property testing, Young's Modulus testing, rheological properties, Poisson's Ratio, API testing, and combinations thereof.
 8. The method of claim 1 further comprising generating a statistical table comprising two or more different parameters of the solid particulates.
 9. The method of claim 8, wherein the different parameters comprise the water requirement and reactive index.
 10. The method of claim 1, further comprising introducing the wellbore treatment fluid into a well bore.
 11. The method of claim 10, wherein the wellbore treatment fluid is introduced into the wellbore using one or more pumps.
 12. The method of claim 1, further comprising mixing components of the wellbore treatment fluid using mixing equipment, the components comprising the two or more solid particulates.
 13. A method of improving a wellbore treatment fluid, the method comprising: calculating a compressive strength requirement using a target Young's modulus as an input in a correlation comprising compressive strength, Young's modulus, and at least one constant; selecting a target reactive index for the wellbore treatment fluid based on the compressive strength requirement; generating the wellbore treatment fluid based on the target reactive index; adjusting the at least one constant from the correlation based on a compressive strength measurement, Young's modulus measurement, or both of the wellbore treatment fluid to generate an updated at least one constant; calculating a second compressive strength requirement using the target Young's modulus as an input in a correlation comprising compressive strength, Young's modulus, and updated at least one constant; selecting a second target reactive index for the wellbore treatment fluid based on the second compressive strength requirement; generating a second wellbore treatment fluid based on the second target reactive index.
 14. The method of claim 13 wherein the correlation is YM=A_(ym)*f(ρ)*g(CS) where YM is Young's modulus, f(ρ) is a function with density as an input, and g(CS) is a function with compressive strength as an input.
 15. The method of claim 13 wherein the target reactive index is calculated at a bottom hole circulating temperature.
 16. The method of claim 13 wherein the second wellbore treatment fluid further comprises at least one additive selected from the group consisting of weighting agents, retarders, accelerators, activators, gas control additives, lightweight additives, gas-generating additives, mechanical-property-enhancing additives, lost-circulation materials, filtration-control additives, fluid-loss-control additives, defoaming agents, foaming agents, transition time modifiers, dispersants, thixotropic additives, suspending agents, and combinations thereof.
 17. The method of claim 13 further comprising calculating a cost of the wellbore treatment fluid.
 18. A system for generating a wellbore treatment fluid comprising: a model correlation comprising compressive strength, Young's modulus, and at least one constant; a plurality of solid particulates; and a computer system operable to accept a target Young's modulus input from a user and generate the wellbore treatment fluid using the target Young's modulus input to the model correlation, wherein the wellbore treatment fluid comprises at least two solid particulates selected form the plurality of solid particulates and wherein a concentration of each of the at least two solid particulates is based on a target property.
 19. The system of claim 18 wherein the correlation is YM=A_(ym)*f(ρ)*g(CS) where YM is Young's modulus, f(ρ) is a function with density as an input, and g(CS) is a function with compressive strength as an input.
 20. The system of claim 18 wherein the computer system is further operable to improve the wellbore treatment fluid by calculating a reactive index and adjusting a relative amount of each of the solid particulates to meet or exceed the target property.
 21. The system of claim 18 further comprising a database, wherein the database comprises the solid particulates, a cost corresponding to each of the solid particulates, a water requirement for each component, and a reactive index for each component.
 22. The system of claim 21 wherein the reactive index is defined by a user or automatically selected by the computer system.
 23. The system of claim 18 wherein the computer system is configured to select an additive to include in the wellbore treatment fluid, wherein the additive comprises at least one additive selected from the group consisting of weighting agents, retarders, accelerators, activators, gas control additives, lightweight additives, gas-generating additives, mechanical-property-enhancing additives, lost-circulation materials, filtration-control additives, fluid-loss-control additives, defoaming agents, foaming agents, transition time modifiers, dispersants, thixotropic additives, suspending agents, and combinations thereof.
 24. The system of claim 18 wherein the computer system is further operable to select the solid particulates based on a water requirement. 